1. Field of the Invention
The present invention relates to a method and an apparatus for optimizing a control module for controlling a controlled system, and a cooperative method for optimization in a method for optimizing a characteristic of the control module.
2. Description of the Related Art
In the past, optimal values of a characteristic of a control module (namely, parameter values for deciding input-output relationship of the control module) to control a controlled system were determined by experiment at the stages of design or setting before shipment, so that users of a product comprising a controlled system were assumed and the users"" characteristics (preference, technique, personality, and use) could be met.
However, with the diversity and advancement of recent technology, the conventional method of deciding optimal values of a characteristic of the control module by experiment brings about difficulty for optimizing the control module, and requires a lot of time. Since personal characteristics or preferences vary from one person to another, the conventional control method cannot provide a characteristic of products which satisfy all users. To solve the problem, there is proposed an evolutionary control system that comprises a basic control module which determines a control output of a controlled system based on predetermined input information, a compensation control module which determines a compensation value for the output of the basic control module, and an evolutionary control module which determines the input-output relationship of the compensation control module by a hereditary algorithm according to the user""s intention. The system learns as a teacher data the input-output relationship through which the compensation control module is optimized by an optimal control module.
The system optimizes the input-output relationship of the compensation control module by the evolutionary control module under user""s direct instruction as the user""s intention, reflecting the compensation control module, which enables each user to obtain a preferred characteristic of the control module in accordance with his feelings. The use of a hereditary algorithm realizes a simple and short-time optimization.
However, the evolutionary control system had the problem that since the input-output relationship of the compensation control module was optimized by the evolutionary control module and the compensation control module was supposed to learn the optimized input-output relationship, it took some time for learning and it also took some time for the optimized characteristic to be reflected to the controlled variable. The system also had the problem that operation was complex.
The object of the present invention is, by solving the problems in the prior art, to reflect the optimized characteristic to the controlled system in a short period of time and to provide a method and an apparatus for optimizing an overall characteristic which simplify the operation.
Moreover, a characteristic optimizing method in prior art has the problem that with regard to a controlled system, a fuel injector, since a plurality of characteristics-fuel consumption performance and drivability performance-are independently optimized, when fuel consumption performance is improved, drivability performance becomes lower, and vice versa, which is a trade-off of optimization of both characteristics. When a plurality of control modules required for controlling a device or controlled system are used, output of manipulated variables of the device and the characteristics of each control module are optimized independently, and thus the same problems as above are raised.
An object of a cooperative method for optimization in a method for optimizing a characteristic is to solve the disadvantage of the prior art and to provide a method for cooperation in order to optimize a plurality of characteristics despite the presence of a trade-off.
The present invention provides a method for optimizing overall characteristics of a device. The method controls performance of a device, which performance is controlled essentially by at least one control module having an input-output relationship regulated by control parameters. In an embodiment, the method comprises the steps of: (a) preselecting values of the control parameters and activating the device; (b) on-line changing values of the control parameters within predetermined ranges under predetermined coding rules; (c) on-line evaluating the performance of the device based on signals indicative of the performance; (d) on-line selecting values of the control parameters based on the evaluation outcome; and (e) repeating steps (b) through (d) while operating the device until desired performance of the device is demonstrated, wherein the at least one control module is optimized. In the above, in another embodiment, at least two control modules control performance of the device, and optimization by steps (a) through (d) is conducted on each control module in repetitive sequence. In the above, xe2x80x9con-linexe2x80x9d means operation on a real-time basis.
In the above, in an embodiment, the device is a control module for controlling another device.
According to the present invention, the problems described above can be resolved.
The present invention can include the following embodiments:
The method optimizes control parameters in a regular control module (i.e., a control module essentially required for controlling a device or system), using an optimization method directly, that determines an output associated with a manipulated variable of a controlled system based on predetermined input information. In the above, the device can be another control module.
The method is the optimization method that uses heuristics.
The method provides an optimal control module for performing said optimization, and after finishing optimal process in said optimal control module, updates the control parameters of the regular control module to the optimized control parameters. The method, in addition, learns the control parameters optimized to the regular control module.
The method provides said regular control module with a control module for executing control and a control module for learning, and after said control module for learning has learned the optimized control parameters, switches said control module for executing control for said control module for learning.
The method provides an optimal control module for outputting the control parameters of the regular control module based on predetermined input information, and optimizes the control parameters of the regular control module by optimizing said optimal control module.
The method uses an algorithm, when the regular control module changes at least part of the control parameters, that can predict influence to other control parameters by the change, uses an algorithm, when the regular control module changes at least part of the control parameters, that can predict influence to the output of the control module by the change, and uses an algorithm that has a linear input-output relation.
The method, as said optimization method, uses an evolutionary calculation method, an adjacent search method and/or an enforced learning method. The evolutionary calculation method includes, for example, a hereditary algorithm, an evolutionary strategy or an evolutionary programming. The adjacent search method includes, for example, an simulated annealing, a hill climbing, a random walk, and a TABU search. The enforced learning method includes, for example, a Q learning or a classifier system.
Said regular control module is the control module which outputs the manipulated variable of the controlled system based on predetermined input information, and inputs a manipulated variable for a user and outputs a manipulated variable for the controlled system.
Said controlled system is a means for controlling performance of a final controlled system, and said final controlled system is a motor, a prime mover, or a combination of a motor and a prime mover.
When said means for controlling performance of a final controlled system is a electronic throttle, said regular control module inputs a manipulated variable of a throttle lever and outputs a manipulated variable of an intake air amount changing means. Said regular control module has control parameters regarding a static characteristic of the manipulated variable of an intake air amount changing means about the manipulated variable of a throttle lever, and control parameters regarding a dynamic characteristic of the manipulated variable of an intake air amount changing means about the manipulated variable of a throttle lever, as a first-order lag time constant and/or an acceleration compensation coefficient that are/is added.
Said regular control module is that control module which outputs a compensated value or a compensation ratio regarding the manipulated variable of a controlled system based on predetermined input information.
Said controlled system is a means for controlling performance of a final controlled system, is a motor, a prime mover, or a combination of a motor and a prime mover, and can be, for example, an electronic control fuel injector or a non-stage transmission. For example, when said controlled system is an electronic control fuel injector, said regular control module outputs a compensation value or compensation ratio about a basic fuel injection amount to the injector based on input information.
When a controlled system is a non-stage transmission, said regular control module outputs a compensation value or compensation ratio about a gear ratio of the non-stage transmission based on input information.
Said optimization is made based on evaluation under user""s intention and/or predetermined evaluation reference. When evaluation reference is predetermined, said evaluation reference is set based on a basic characteristic of a controlled system with aging deterioration or regulation. about a controlled system.
In addition, evaluation can be combined, by setting beforehand the evaluation reference based on a regulation about a controlled system, preparing for evaluation under user""s intention within a range of the evaluation reference, and optimizing the characteristic according to user""s preference within the regulation.
To attain the object, an apparatus for optimizing an overall characteristic of the invention comprises a regular control unit including a regular control module which determines an output associated with a manipulated variable of a controlled system based on predetermined input information, and an optimal process unit for directly optimizing control parameters of said regular control module using an optimization method having heuristics.
Said optimal process unit includes an optimal operation device which performs operation on a optimization method, and an automatic evaluation device which conducts evaluation on optimal process based on evaluation reference set beforehand, whereby said optimal process controls control parameters obtained from the optimal operation by using the regular control module and optimization is proceeded with the result evaluated by the automatic evaluation device.
Said optimal process unit includes an optimal operation device which performs operation on a optimization method, and means for inputting evaluation based on user""s intention on optimal process, whereby said optimal process controls control parameters obtained from the optimal operation by using the regular control module, and optimization is proceeded with the result evaluated by the automatic evaluation device.
Said optimal process unit includes an optimal operation device which performs operation on a optimization method, an optimal module for outputting values of the control parameters of the regular control module based on predetermined input information, and an automatic evaluation device which conducts evaluation on optimal process based on evaluation reference set beforehand, whereby said optimal process controls control parameters obtained from the optimal module by using the regular control module, and optimization of the optimal module is proceeded, with the result evaluated by the automatic evaluation device, so that optimal control parameters from the optimal module can be obtained.
Said optimal process unit includes an optimal operation device which performs operation on a optimization method, an optimal module for outputting values of the control parameters of the regular control module based on predetermined input information, and means for inputting evaluation based on user""s intention on optimal process, whereby said optimal process controls control parameters obtained from the optimal module by using the regular control module, and optimization of the optimal module is proceeded, with the result evaluated by the automatic evaluation device, so that optimal control parameters from the optimal module can be obtained.
Said optimal operation device conducts operation on optimization by using an evolutionary calculation method, an adjacent search method and/or an enforced learning method.
Moreover, to accomplish the object, a cooperative method for optimization in a method for optimizing a characteristic comprises the steps of optimizing each characteristic of a plurality of regular control modules that determine an output associated with a manipulated variable of a controlled system based on predetermined input information, and after optimizing one regular control module, optimizing other regular control modules so that an obtained characteristic can be improved or maintained.
A cooperative method for optimization in a method for optimizing a characteristic comprising the steps of optimizing each characteristic of a plurality of regular control modules that determine an output associated with a manipulated variable of a controlled system based on predetermined input information, and optimizing a plurality of regular control modules at a interval so that obtained characteristics can be improved or maintained.
A cooperative method for optimization in a method for optimizing a characteristic comprising the steps of optimizing each characteristic of a plurality of regular control modules that determine an output associated with a manipulated variable of a controlled system based on predetermined input information, and during optimizing one regular control module, optimizing other regular control modules in parallel so that obtained characteristics the regular control module obtained can be improved or maintained.
A cooperative method for optimization in a method for optimizing a characteristic comprising the steps of optimizing each characteristic of a plurality of regular control modules that determine an output associated with a manipulated variable of a controlled system based on predetermined input information, and optimizing a plurality of regular control modules in parallel so that obtained characteristics can be improved or maintained.
The cooperative method comprises the steps of, for optimizing at least one of the regular control modules, using an automatic evaluation method which evaluates during optimization based on evaluation reference set beforehand, and for optimizing other regular control modules, using an interactive evaluation method which evaluates during optimization based on evaluation under user""s intention.
In the cooperative method, said evaluation reference is set based on a reference characteristic of a controlled system having aging deterioration or a regulation of a controlled system. In addition, evaluation can be combined by beforehand setting the evaluation reference based on the regulation regarding one controlled variable, evaluating within a range of the evaluation reference under user"" preference, and optimizing characteristics within a range of a regulation according to user""s preference.
A cooperative method for optimization in a method for optimizing a characteristic comprises the steps of optimizing each of a plurality of characteristics of regular control modules that determine an output associated with a manipulated variable of a controlled system based on predetermined input information, and after optimizing other characteristics, optimizing other regular control modules so that an obtained characteristic can be improved or maintained.
A cooperative method for optimization in a method for optimizing a characteristic comprises the steps of optimizing each of a plurality characteristics of the regular control modules that determine an output associated with a manipulated variable of a controlled system based on predetermined input information, and optimizing a plurality of characteristics at a interval so that obtained characteristics can be improved or maintained.
A cooperative method for optimization in a method for optimizing a characteristic comprises the steps of optimizing each of a plurality characteristics of the regular control modules that determine an output associated with a manipulated variable of a controlled system based on predetermined input information, and during optimizing one characteristic, optimizing other characteristics in parallel so that the characteristic can be improved or maintained.
A cooperative method for optimization in a method for optimizing a characteristic comprises the steps of optimizing each of a plurality of characteristics of the regular control modules that determine an output associated with a manipulated variable of a controlled system based on predetermined input information, and optimizing a plurality of characteristics in parallel so that obtained characteristics can be improved or maintained.
The cooperative method comprises the steps of, for optimizing at least one of the regular control modules, using an automatic evaluation method which evaluates during optimization based on evaluation reference set beforehand, and for optimizing other regular control modules, using an interactive evaluation method which evaluates during optimization based on evaluation under user""s intention.
In the cooperative method, said evaluation reference is set based on a reference characteristic of a controlled system having aging deterioration or a regulation of a controlled system. In addition, evaluation can be combined by beforehand setting the evaluation reference based on the regulation regarding one controlled variable, evaluating within a range of the evaluation reference under user"" preference, and optimizing characteristics within a range of a regulation according to user""s preference.